Render lighting dataset: A collection of rendered images with varied lighting conditions using blender render engines

The quality of datasets is crucial in computer graphics and machine learning research and development. This paper presents the Render Lighting Dataset, featuring 63,648 rendered images of Blender's primitive shapes with various lighting conditions and engines. The images were created using Blender 4.0′s Cycles and Eevee Render Engines, with careful attention to detail in texture mapping and UV unwrapping. The dataset covers six different lighting conditions, including Area Light, Spotlight, Point Light, Tri-Light, HDRI (Sunlight), and HDRI (Overcast), each adjusted using Blender's different options in the Color Management panel. With thirteen unique materials, ranging from Coastal Sand to Glossy Plastic, the dataset provides visual diversity for researchers to explore material properties under different lighting conditions using different render engines. This dataset serves as a valuable resource for researchers looking to enhance 3D rendering engines. Its diverse set of rendered images under varied lighting conditions and material properties allows researchers to benchmark and evaluate the performance of different rendering engines, develop new rendering algorithms and techniques, optimize rendering parameters, and understand rendering challenges. By enabling more realistic and efficient rendering, advancing research in lighting simulation, and facilitating the development of AI-driven rendering techniques, this dataset has the potential to shape the future of computer graphics and rendering technology.


a b s t r a c t
The quality of datasets is crucial in computer graphics and machine learning research and development.This paper presents the Render Lighting Dataset, featuring 63,648 rendered images of Blender's primitive shapes with various lighting conditions and engines.The images were created using Blender 4.0 s Cycles and Eevee Render Engines, with careful attention to detail in texture mapping and UV unwrapping.The dataset covers six different lighting conditions, including Area Light, Spotlight, Point Light, Tri-Light, HDRI (Sunlight), and HDRI (Overcast), each adjusted using Blender's different options in the Color Management panel.With thirteen unique materials, ranging from Coastal Sand to Glossy Plastic, the dataset provides visual diversity for researchers to explore material properties under different lighting conditions using different render engines.This dataset serves as a valuable resource for researchers looking to enhance 3D rendering engines.Its diverse set of rendered images under varied lighting conditions and material properties allows researchers to benchmark and evaluate the performance of different rendering engines, develop new rendering algorithms and techniques, optimize rendering parameters, and understand rendering challenges.By enabling more realistic and efficient rendering, advancing research in lighting simulation, and facilitating the development of AI-driven rendering techniques, this dataset has the potential to shape the future of computer graphics and rendering technology.
© 2024 The Author(s).Published by Elsevier Inc.This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ ) Specifications Table

Value of the Data
• Researchers can use this dataset to develop and test new rendering techniques, including real-time rendering algorithms, by analyzing the interplay of light and material under various conditions.• The Render Lighting Dataset can be a standard benchmark for machine learning algorithms focused on image recognition, lighting estimation, and material property analysis.Its consistent and controlled variables allow for objective comparison of algorithm performance.
• The inclusion of different materials offers a rich resource for researchers to understand and model the visual properties of materials under diverse lighting conditions.• The dataset provides a diverse set of images that can be used to train machine learning models to recognize different 3D shapes, lighting conditions, and material textures, which is crucial in computer vision and graphics applications.• It can be used as an educational tool for students learning about computer graphics, providing hands-on experience with a dataset that demonstrates fundamental principles of lighting and material in rendering.

Background
Computer graphics have come a long way and are now in high demand for creating computer-generated visuals in movies, advertisements, product designs, and other fields.Render engines play a vital role in turning project ideas into real products.Different engines can produce different results, which raises the question of how to improve them [1] .Blender has two primary render engines, Eevee and Cycles, both of which are great and excel in specific areas.Eevee is faster, while Cycles produces superior quality, highlighting the trade-offs in rendering approaches [2] .Lighting is crucial to determine an object's realism, and improving lighting is a big challenge, especially in 3D rendering engines involving Virtual Reality (VR) and Augmented Reality (AR).To mimic real-world lighting and material accuracy in rendering engines and for object detection and tracking, diverse datasets are critical [3] .This context enriches the significance of the Render Lighting Dataset [4] as a benchmark for evaluating and improving rendering algorithms, catering to the nuanced demands of different rendering engines across various industries.

Experimental Design, Materials and Methods
The main objective of this dataset was to create a repository of rendered images using Blender software to assist researchers in enhancing 3D rendering engines.The dataset can also be utilized for various purposes such as machine learning, artificial Intelligence, computer vision, and pattern recognition and detection and can also be utilized in projects dealing with computer-simulated virtual worlds.

Shape design
To create the images, we started by creating shapes and an environment in which to render them.Instead of using default primitive shapes, we edited them to improve texture mapping.The background was a white plane inside a smooth sphere.Table 1 provides a detailed specification of each shape used in the dataset.
In order to understand the topology of the shapes better, a wireframe view of each shape has been included in Fig. 5 .

Lighting setups
Afterward, we proceeded to arrange the lighting and camera for the shoot.To set up the HDRI, we rotated it positively by 60 °in the Z axis and 2 K resolution HDRI maps were used.As for the point light, spotlight, area light, and tri lights, we positioned them in one corner so that one side receives more light than the others.For the light sources that can be adjusted, we aimed them at the center of the object.The point light, spotlight, and area light were all set to a power of 100 W, and a pure white color was used for each of them.The spotlight was given  a spot size of 60 °and a blend of 0.150 units while the area light was given a size of 2 m.The shadow caustics were disabled, and multiple importance was enabled for all light sources.As for the tri lights, each of them was given a unique intensity and color.The backlight was set to a light blue color (Hex: #D1F7FF) and an intensity of 35 W. The fill light was given a pure white color with an intensity of 25 W, while the Key light was also set to a pure white color with a high intensity of 100 W. The lighting setup for these four non-HDRI light sources can be observed in Fig. 6 .

Material design
Next, we prepared the materials for the shapes.We gathered the materials from various online resources that are free to use and set them up utilizing Blender's nodes.Our main focus was on the base color (diffuse) map, roughness map, normal map (OpenGL), displacement map,   and metalness map.All the texture maps utilized in the renders are in 2 K resolution.All of the shader setups are similar, however, the shader setup for glass differs slightly due to the way Blender's Cycles and Eevee render engines handle transparent and translucent materials.In Eevee, the blend mode of the glass shader was set to 'Alpha Blend', and the Shadow mode was set to 'Opaque'.

Render engine parameters
In the render engine settings, the screen space refraction and subsurface translucency were turned off, and no bloom or ambient occlusion was used.In eevee, the render sample count was set to 16 with the remaining settings set to default.For Cycles, the render sample count was also set to 16, the noise threshold was set to 0.0100, and denoising was enabled with the denoiser set to 'OpenImageDenoise'.Passes were set to 'Albedo and Normal', and the prefilter was set to 'Accurate' while the rest of the settings were left default.The color management settings were adjusted between View Transform set to AGX and Filmic and Look set to None, Punchy, and High-Contrast respectively.The punchy option is only available with the latest AGX view transform option, so for the filmic view transform, a high-contrast look was used instead as an alternative.

Camera setups
Finally, we adjusted the camera and angles.We used a perspective-type camera with a 24 mm focal length and clip start set to 0.01 and end set to 10 0 0 m.We didn't use any depth of field.To capture the light from different angles, we used 17 different camera angles by adjusting the X-axis and Z-axis rotations while keeping the Y-axis rotation at 0 °.A detailed specification of the camera angles used is provided in Table 2 .

Fig. 1 .
Fig. 1.The file structure of the Render Lighting dataset along with the number of folders.

Fig. 2 .
Fig. 2. The simplified file structure of the Render Lighting dataset along with the number of folders inside each subfolder.

Fig. 3 .
Fig. 3. Brushed steel cube rendered with cycles using HDRI overcast lighting and AGX punchy settings.

Table 1 Fig. 5 .
Fig. 5. Wireframe view of each shape used in the dataset.

Table 2
Specifications for each camera angle.